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scientifique

Temporal mosaicking approaches of Sentinel-2 images for extending topsoil organic carbon content mapping in croplands / Emmanuelle Vaudour in International journal of applied Earth observation and geoinformation, vol 96 (April 2021)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 96 (April 2021) . - n° 102277 Titre : Temporal mosaicking approaches of Sentinel-2 images for extending topsoil organic carbon content mapping in croplands Type de document : Article/Communication Auteurs : Emmanuelle Vaudour, Auteur ; Cécile Gomez, Auteur ; Philippe Lagacherie, Auteur Année de publication : 2021 Article en page(s) : n° 102277 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] humidité du sol [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] mosaïquage d'images [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] puits de carbone [Termes IGN] réflectance spectrale [Termes IGN] série temporelle [Termes IGN] sol nu [Termes IGN] surface cultivée [Termes IGN] teneur en carbone [Termes IGN] terre arable [Termes IGN] Yvelines (78) Résumé : (auteur) The spatial assessment of soil organic carbon (SOC) is a major environmental challenge, notably for evaluating soil carbon stocks. Recent works have shown the capability of Sentinel-2 to predict SOC content over temperate agroecosystems characterized with annual crops. However, because spectral models are only applicable on bare soils, the mapping of SOC is often obtained on limited areas. A possible improvement for increasing the number of pixels on which SOC can be retrieved by inverting bare soil reflectance spectra, consists of using optical images acquired at several dates. This study compares different approaches of Sentinel–2 images temporal mosaicking to produce a composite multi-date bare soil image for predicting SOC content over agricultural topsoils. A first approach for temporal mosaicking was based on a per-pixel selection and was driven by soil surface characteristics: bare soil or dry bare soil with/without removing dry vegetation. A second approach for creating composite images was based on a per-date selection and driven either by the models performance from single-date, or by average soil surface indicators of bare soil or dry bare soil. To characterize soil surface, Sentinel-1 (S1)-derived soil moisture and/or spectral indices such as normalized difference vegetation index (NDVI), Normalized Burn Ratio 2 (NBR2), bare soil index (BSI) and a soil surface moisture index (S2WI) were used either separately or in combination. This study highlighted the following results: i) none of the temporal mosaic images improved model performance for SOC prediction compared to the best single-date image; ii) of the per-pixel approaches, temporal mosaics driven by the S1-derived moisture content, and to a lesser extent, by NBR2 index, outperformed the mosaic driven by the BSI index but they did not increase the bare soil area predicted; iii) of the per-date approaches, the best trade-off between predicted area and model performance was achieved from the temporal mosaic driven by the S1-derived moisture content (R2 ~ 0.5, RPD ~ 1.4, RMSE ~ 3.7 g.kg-1) which enabled to more than double (*2.44) the predicted area. This study suggests that a number of bare soil mosaics based on several indicators (moisture, bare soil, roughness…), preferably in combination, might maintain acceptable accuracies for SOC prediction whilst extending over larger areas than single-date images. Numéro de notice : A2021-238 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102277 Date de publication en ligne : 14/12/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102277 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97258 [article]

Du drone LiDAR à un nuage de points précis et exact : une chaîne de traitement LiDAR adaptée et quasi automatique / Maxime Lafleur in XYZ, n° 165 (décembre 2020)

Public [article]  inXYZ > n° 165 (décembre 2020) . - pp 25 -32 Titre : Du drone LiDAR à un nuage de points précis et exact : une chaîne de traitement LiDAR adaptée et quasi automatique Type de document : Article/Communication Auteurs : Maxime Lafleur, Auteur ; Elliot Mugner, Auteur ; Rabine Keyetieu-Nlowe, Auteur ; Nicolas Seube, Auteur Année de publication : 2020 Article en page(s) : pp 25 -32 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] auscultation d'ouvrage [Termes IGN] barrage [Termes IGN] base de données localisées 3D [Termes IGN] chaîne de traitement [Termes IGN] données lidar [Termes IGN] drone [Termes IGN] exactitude des données [Termes IGN] filtrage du bruit [Termes IGN] géoréférencement [Termes IGN] Haute-Loire (43) [Termes IGN] précision des données [Termes IGN] semis de points [Termes IGN] sol nu Résumé : (Auteur) Le levé LiDAR présenté dans cet article a été effectué dans le cadre d’une mission d’évaluation de la chaîne de traitement mdInfinity, appliquée à des données acquises par un système drone LiDAR Microdrones. Les différents outils qui constituent cette chaîne de traitement ont été développés et intégrés sur la plateforme de traitement mdInfinity dans une version particulièrement adaptée au système de levé utilisé pour cette mission. Le site utilisé pour cette évaluation est le barrage de Labrioulette (Haute-Garonne), infrastructure située sur la Garonne et exploitée par EDF. Cette zone contient de nombreux éléments sur lesquels la précision et l’exactitude des données LiDAR est primordiale afin d’obtenir un nuage de point exploitable ; notamment la complexité structurelle du barrage (figure 1), les zones sous couvert végétal dense, l’aire de transformation électrique, etc. Pour cette raison, en plus de confirmer la bonne interopérabilité des systèmes LiDAR Microdrones avec les outils de traitement mdInfinity, nous avons tiré profit de cette acquisition pour évaluer les performances de nos algorithmes. Numéro de notice : A2020-770 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96662 [article]

Exemplaires(1)

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112-2020041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Retrieving soil surface roughness with the Hapke photometric model: Confrontation with the ground truth / Sébastien Labarre in Remote sensing of environment, vol 225 (May 2019)  

Public [article]  inRemote sensing of environment > vol 225 (May 2019) . - pp 1 - 15 Titre : Retrieving soil surface roughness with the Hapke photometric model: Confrontation with the ground truth Type de document : Article/Communication Auteurs : Sébastien Labarre, Auteur ; Stéphane Jacquemoud, Auteur ; Cécile Ferrari, Auteur ; Arthur Delorme, Auteur ; Allan Derrien, Auteur ; Raphaël Grandin, Auteur ; Mohamed Jalludin, Auteur ; F. LemaÎtre, Auteur ; Marianne Metois, Auteur ; Marc Pierrot-Deseilligny , Auteur ; Ewelina Rupnik , Auteur ; Bernard Tanguy, Auteur Année de publication : 2019 Projets : CAROLInA / Jacquemoud, Stéphane Article en page(s) : pp 1 - 15 Note générale : Bibliographie The PhD thesis of Sébastien Labarre was funded by the Direction générale de l'armement (DGA) and by the Commissariat à l'énergie atomique et aux énergies alternatives (CEA). Field data were acquired in the frame of the CAROLInA (Characterization of Multi-Scale Roughness using OpticaL ImAgery) project funded by CNES. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Djibouti [Termes IGN] goniomètre [Termes IGN] image optique [Termes IGN] image Pléiades-HR [Termes IGN] modèle numérique de surface [Termes IGN] réflectance du sol [Termes IGN] rugosité du sol [Termes IGN] sol nu Résumé : (Auteur) Surface roughness can be defined as the mean slope angle integrated over all scales from the grain size to the local topography. It controls the energy balance of bare soils, in particular the angular distribution of scattered and emitted radiation. This provides clues to understand the intimate structure and evolution of planetary surfaces over ages. In this article we investigate the capacity of the Hapke photometric model, the most widely used in planetary science, to retrieve surface roughness from multiangular reflectance data. Its performance is still a question at issue and we lack validation experiments comparing model retrievals with ground measurements. To address this issue and to show the potentials and limits of the Hapke model, we compare the mean slope angle determined from very high resolution digital elevation models of volcanic and sedimentary terrains sampled in the Asal-Ghoubbet rift (Republic of Djibouti), to the photometric roughness estimated by model inversion on multiangular reflectance data measured on the ground (Chamelon field goniometer) and from space (Pleiades images). The agreement is good on moderately rough surfaces, in the domain of validity of the Hapke model, and poor on others. Numéro de notice : A2019-154 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2019.02.014 Date de publication en ligne : 02/03/2019 En ligne : https://doi.org/10.1016/j.rse.2019.02.014 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92492 [article]

Unmixing polarimetric radar images based on land cover type identified by higher resolution optical data before target decomposition: application to forest and bare soil / Sébastien Giordano in IEEE Transactions on geoscience and remote sensing, vol 56 n° 10 (October 2018)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 56 n° 10 (October 2018) . - pp 5850 - 5862 Titre : Unmixing polarimetric radar images based on land cover type identified by higher resolution optical data before target decomposition: application to forest and bare soil Type de document : Article/Communication Auteurs : Sébastien Giordano , Auteur ; Grégoire Mercier, Auteur ; Jean-Paul Rudant , Auteur Année de publication : 2018 Projets : 1-Pas de projet / Jacquemoud, Stéphane Article en page(s) : pp 5850 - 5862 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse des mélanges spectraux [Termes IGN] analyse linéaire des mélanges spectraux [Termes IGN] biomasse aérienne [Termes IGN] décomposition spectrale [Termes IGN] données polarimétriques [Termes IGN] forêt [Termes IGN] image Radarsat [Termes IGN] matrice de covariance [Termes IGN] occupation du sol [Termes IGN] polarimétrie radar [Termes IGN] sol nu [Termes IGN] surface forestière Résumé : (auteur) Extracting information from a polarimetric radar representation usually consists in decomposing it with target decomposition algorithms. This first step can be seen as a geometric analysis of the polarimetric information: the identification of physical radar scattering mechanisms. The problem is that average physical parameters are estimated. As a consequence, these parameters might not describe correctly any of the land cover types that can be mixed together into the radar resolution cell. Therefore, using the polarimetric parameters for land cover classification is challenging. The novelty of the method is to propose a thematic analysis of the polarimetric information preceding the geometric one. The objective is to assess if splitting off polarimetric information on a land cover type basis before applying usual target decomposition algorithms can produce more consistent radar scattering mechanisms when land cover classes are mixed inside the radar resolution cell. A cooperative fusion framework in which very high-resolution optical images are used to unmix physical radar scattering mechanisms is proposed. For bare soil and forests, we point out that a linear unmixing model applied to the covariance matrix is able to split off polarimetric information on a land cover type basis. The assessment of the unmixed radar matrices is carried out with polarimetric radar images from the Radarsat-2 satellite. It was found that despite speckle, the reconstructed radar information after the unmixing process is statistically relevant with the observations. The question whether the unmixed radar images contain relevant thematic information is more challenging, but results tend to validate this property. This method could be used to have a better estimation of vegetation biomass in the context of open forested areas. Numéro de notice : A2018-331 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2827258 Date de publication en ligne : 09/07/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2827258 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90475 [article]

Sensitivity of spectral reflectance values to different burn and vegetation ratios: A multi-scale approach applied in a fire affected area / Magdalini Pleniou in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 79 (May 2013) . - pp 199 - 210 Titre : Sensitivity of spectral reflectance values to different burn and vegetation ratios: A multi-scale approach applied in a fire affected area Type de document : Article/Communication Auteurs : Magdalini Pleniou, Auteur ; Nikos Koustias, Auteur Année de publication : 2013 Article en page(s) : pp 199 - 210 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] affinage d'image [Termes IGN] analyse comparative [Termes IGN] classification par maximum de vraisemblance [Termes IGN] Grèce [Termes IGN] image Ikonos [Termes IGN] image Landsat-SWIR [Termes IGN] image Terra-ASTER [Termes IGN] incendie de forêt [Termes IGN] rayonnement proche infrarouge [Termes IGN] régression multiple [Termes IGN] sol nu Résumé : (Auteur) The aim of our study was to explore the spectral properties of fire-scorched (burned) and non fire-scorched (vegetation) areas, as well as areas with different burn/vegetation ratios, using a multisource multiresolution satellite data set. A case study was undertaken following a very destructive wildfire that occurred in Parnitha, Greece, July 2007, for which we acquired satellite images from LANDSAT, ASTER, and IKONOS. Additionally, we created spatially degraded satellite data over a range of coarser resolutions using resampling techniques. The panchromatic (1 m) and multispectral component (4 m) of IKONOS were merged using the Gram-Schmidt spectral sharpening method. This very high-resolution imagery served as the basis to estimate the cover percentage of burned areas, bare land and vegetation at pixel level, by applying the maximum likelihood classification algorithm. Finally, multiple linear regression models were fit to estimate each land-cover fraction as a function of surface reflectance values of the original and the spatially degraded satellite images. The main findings of our research were: (a) the Near Infrared (NIR) and Short-wave Infrared (SWIR) are the most important channels to estimate the percentage of burned area, whereas the NIR and red channels are the most important to estimate the percentage of vegetation in fire-affected areas; (b) when the bi-spectral space consists only of NIR and SWIR, then the NIR ground reflectance value plays a more significant role in estimating the percent of burned areas, and the SWIR appears to be more important in estimating the percent of vegetation; and (c) semi-burned areas comprising 45–55% burned area and 45–55% vegetation are spectrally closer to burned areas in the NIR channel, whereas those areas are spectrally closer to vegetation in the SWIR channel. These findings, at least partially, are attributed to the fact that: (i) completely burned pixels present low variance in the NIR and high variance in the SWIR, whereas the opposite is observed in completely vegetated areas where higher variance is observed in the NIR and lower variance in the SWIR, and (ii) bare land modifies the spectral signal of burned areas more than the spectral signal of vegetated areas in the NIR, while the opposite is observed in SWIR region of the spectrum where the bare land modifies the spectral signal of vegetation more than the burned areas because the bare land and the vegetation are spectrally more similar in the NIR, and the bare land and burned areas are spectrally more similar in the SWIR. Numéro de notice : A2013-237 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.02.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.02.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32375 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2013051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Prediction of the error induced by topography in satellite microwave radiometric observations / Luca Pulvirenti in IEEE Transactions on geoscience and remote sensing, vol 49 n° 9 (September 2011)  

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Terrestrial laser scan error in the presence of dense ground vegetation / S. Coveney in Photogrammetric record, vol 26 n° 135 (September - November 2011)  

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Land surface emissivity retrieval from combined mid-infrared and thermal infrared data of MSG-SEVIRI / G.M. Jiang in Remote sensing of environment, vol 105 n° 4 (30/12/2006)  

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Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes / X.L. Chen in Remote sensing of environment, vol 104 n° 2 (30 September 2006)  

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Evaluation of a rough soil surface description with ASAR-ENVISAT radar data / Mehrez Zribi in Remote sensing of environment, vol 95 n° 1 (15/03/2005)  

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Estimation and monitoring of bare soil/vegetation ratio with SPOT vegetation and HRVIR / Grégoire Mercier in IEEE Transactions on geoscience and remote sensing, vol 43 n° 2 (February 2005)  

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Discrimination potential of X-band polarimetric SAR data / Nicolas Baghdadi in International Journal of Remote Sensing IJRS, vol 25 n° 22 (November 2004)  

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A hemispherical-directional reflectance model as a tool for understanding image distinctions between cultivated and uncultivated bare surfaces / J. Cierniewski in Remote sensing of environment, vol 90 n° 4 (30/04/2004)  

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Exploitation d'une image très haute résolution pour la cartographie des plantations et de la végétation naturelle dans la région de Marrakech / Y. Gauthier (2004)

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Influence de la rugosité de surface en radiométrie micro-onde des sols nus / L. Laguerre (1995)

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